SDMXthon: the pythonic SDMX

SDMXthon is a library for parsing, validate and write SDMX documents.

Based on Pandas and written in python, it allows the conversion from different data formats, as CSV or JSON, and inputting the data straight from a Pandas Dataframe.

Features

Reading and writing SDMX-ML and SDMX-CSV
Pandas connector (SDMX to Pandas, Pandas to SDMX)
Data validation
Metadata validation
Interaction with SDMX APIs and Fusion Metadata Registry

Main links

Bug Tracker and Enhancements: https://github.com/Meaningful-Data/sdmxthon/issues
Documentation: https://docs.sdmxthon.meaningfuldata.eu
Source Code: https://github.com/Meaningful-Data/sdmxthon
Changelog: https://docs.sdmxthon.meaningfuldata.eu/changelog.html
PyPi: https://pypi.org/project/sdmxthon/

Installation

To install the library, just run the following command in a terminal:

pip install SDMXthon

It requires at least python 3.8

Introduction

SDMXthon is designed upon the necessity of a python library that guarantees the conversion of data to SDMX and vice versa, supporting many formats.

The philosophy to build it was to provide a simple way to parse and access the data and metadata, perform validations on it, modify the data if necessary using the Pandas infrastructure and provide an engine to write SDMX-ML and SDMX-CSV files.

For a quickstart, please head to the Walkthrough

Main convenience methods

Read SDMX files: read_sdmx
Message (SDMX Message abstraction)
Dataset (data handling, validation and writing SDMX-ML and SDMX-CSV files)
Webservices

Information Model

The library is based on the SDMX Information model. Same names for classes and properties have been used.

Access to the main features of SDMXthon

Access to the main external methods are in API module

Classes of the library are in the Model package